Based on the Clinical Medical Research Information Sharing System ( CMRISS ) , this article took thedisease-syndrome-herb study on acute exacerbation of chronic obstructive pulmonary disease (AECOPD) as a model to explore the establishment of disease-syndrome-herb study method on many types of diseases for the guidance of Chinese medicine clinical practice. The CMRISS of the First Affiliated Hospital of Henan University of Traditional Chinese Medicine, which contained 5000 format electronic medical records from August 2011 to March 2013 , was used as the database . Data preprocessing , crystal reports and complex network were used in data mining to receive the frequency relation of AECOPD disease-syndrome-herb in order to analyze medica-tion features of different Chinese medicine clinical syndromes of AECOPD . The results showed that three syn-dromes, which were phlegm-heat obstructing the lungs, phlegm-stasis obstructing the lungs, and qi-yin deficien-cy, have corresponding Chinese herbs of licorice, orange peel and earthworm. The treatment of syndrome of phlegm-heat obstructing the lungs contains herbs to clear heat, remove phlegm and activate blood circulation. The treatment of syndrome of qi-yin deficiency contains herbs to benefitqi , nourish yin as well as to activate blood circulation and remove phlegm. It was concluded that the application of CMRISS is able to process a large amount of clinical data. The data mining results can be used to guide clinical practice. It provided a better plat-form for the scientific research of Chinese medicine clinical practice .

Clinical cases of TCM are used as important clinical data to record the whole process of the interaction between doctors and patients in the form of text.However,in the context of big data,there is a lack of research on the use of information covered in clinical cases.Therefore,we studied the method of extracting the symptom term from the history of present illness in TCM clinic in this paper,in order to lay the foundation for the further use of clinical cases.First,twelve thousand,three hundred and sixty-seven history data of present illness were obtained by random selection and expert review.According to the different disease types,they were divided into the two groups of the experiments:4,838 data in the diabetes group,7,529 data in the spleen and stomach disease group and 12,367 data in the mixed or combined group.A glossary of symptom terms covering 22,996 words were compiled.Then,five feature templates,such as sliding window feature,prefix and suffix character and lexical features,were selected.CRFs model was adopted to carry out named entity extraction experiment.As a result,in the open test,the performance of diabetes,spleen and stomach disease and mixed group were (0.83,0.8,0.82),(0.9,0.9,0.89) and (0.88,0.87,0.87),respectively,while the results were (0.83,0.82,0.83),(0.95,0.95,0.95) and (0.93,0.92,0.92) in the ten-fold cross validation.In conclusion,the results showed that the CRFs algorithm was an excellent sequence labeling algorithm and applied to the named entity extraction task of symptom history.

This study was aimed to analyze correlation between traditional Chinese medicine (TCM) syndromes and symptoms of acute exacerbation chronic obstructive pulmonary disease (AECOPD) based on complex network in order to provide a scientific basis for TCM syndrome amendments of diagnostic criteria, and explore relevant technologies to promote its application. By way of the current Clinical Research Information Sharing System, data and data pro-cessing were carried out (EHR 3000 between August 2011 and January 2013) into the database by ETL software. The MISCR (correlation between common symptoms and common syndromes) from both common symptoms and com-mon syndromes of AECOPD was analyzed with existing diagnosis standards of AECOPD. The comparative analysis on TCM syndromes such as heat phlegm obstructing the lung, lung and kidney qi deficiency, phlegm turbid obstructing the lung and their correspondent existing diagnosis standards of AECOPD showed that the common TCM syndromes in the clinic are the mixture of deficiency and excess syndromes. However, some individual symptom is contradicted to its correspondent syndrome. It was concluded that based on the Clinical Research Information Sharing System, the research on correlation analysis between syndromes and symptoms of AECOPD can provide strong evidence and methodology for the validation and revision of TCM diagnostic criteria.

Traditional Chinese medicine (TCM) clinical symptoms, which were main evidences in syndrome differentiation and treatment, were also main data in the clinical individual diagnosis and treatment. However, the absence of high-quality symptom ontology was still obvious in TCM clinical and data using. By analyzing the research and data of clinical phenotype ontologies associated with symptoms, this paper was aimed to introduce and sort the existing ontologies, in order to discuss related problems. Furthermore, we provided ideas and expound the importance of building data network of symptoms, diseases, genes, drugs, chemicals, side effects with the data we collected and disposed around symptoms, in order to construct TCM clinical phenotype ontology. We believed that our work will help the development of individual treatment and precision medicine in TCM. It was also the key of individual big data analysis which was urgent need to promote.

How to discover the valuable knowledge from the large amount of prescription data accumulated in the long-term medical practice of traditional Chinese medicine (TCM) is one of the important contents of TCM modernization.Based on the prescription data of Xue' s clinical practice of many years,this paper explored the method of combining TCM network and prescription network to find out Xue' s common core drug combination.Based on 9,584 prescriptions in the Hospital Information System of Guang'anmen Hospital of China Academy of Chinese Medical Sciences,prescription network and drug network were constructed according to the similarity of prescription composition and drug co-occurrence relationship.Using the complex network analysis methods,such as community analysis method,to analyze the prescription and drug compatibility,the results were evaluated and analyzed by Xue and his successors.As a result,through complex network analysis,126 modular prescriptions and 4 TCM modules were obtained.One of the core components of the prescription module included Xiao Chai Hu decoction,Yin Qiao powder,and Sheng Jiang powder compound addition and subtraction.It was in consistent with the drug composition of exogenous febrile prescriptions excavated earlier.In conclusion,using the complex network methods,we can get some core drug combinations prescribed by Prof.Xue,and achieve the common compound core drug combination for treating diseases with certain vantages,laying a foundation for further inheriting and excavating Xue' s effective experience.

"Coming from clinical experiences and serving for the clinical application", which is the basic mode of academic development and technological progress of Chinese medicine. Clinical data embodies clinical experience and medical innovation and technology. Clinical data is also an important carrier to spread Chinese medicine and knowledge wealth for the whole country. The author thoroughly discussed the scientific value, necessity and significance of Chinese medicine clinical data in this article.

Due to the importance of molecular mechanisms of drug actions, network pharmacology has become a new perspective on drug mechanism research and novel drug discovery. Drug target prediction using computational methods, is one of the key research topics in network pharmacology. This paper reviewed the related research on drug target prediction methods. Furthermore, general principles of drug target prediction methods and key steps of them in recent years were summarized. Given the diversity of Chinese medicine ingredients, the network controlla-bility of herbs and the lack of high-quality pharmacological data, the network regulation mechanism of Chinese herb research will meet even more difficulties than modern drug research. Therefore, this paper also discussed main is-sues and research trends of Chinese herb target prediction. Finally, combining with the actual consolidated network data of Chinese herbs, chemical structure similarity computation and link prediction methods, the network-based herb target prediction method was proposed to demonstrate key research steps. Furthermore, we discussed the most significant research topics that we should addressed to enhance the high quality results of herb target prediction.

Real world clinical diagnosis and treatment activity is a complicated decision-making task. The effective clinical cases of traditional Chinese medicine (TCM) of highly experienced physicians play an important role in the routine diagnosis and treatment and the formulation of medical knowledge . Based on TCM electronic medical record data, this paper proposed a decision support prototype system on TCM clinical diagnosis and treatment based on TCM effective clinical cases and case-based reasoning (CBR) algorithm, which is used to assist inexperienced clinicians to make more reliable clinical decisions, and thereafter to improve the clinical curative effectiveness. The system integrates TCM clinical cases data set from a TCM clinical data warehouse, and retrieves the similar cases based on CBR method. In particular, according to the underlying personalized diagnosis and treatment for patients in TCM, this system implemented a flexible diagnosis and treatment modification mechanism based on correlation analysis among symptoms, diagnoses (syndrome or pattern in TCM) and medicine. Finally, through a demonstration of clinical application, we made an initial evaluation of the usefulness and practical effects of the system.

Optimum research on famous TCM doctors’ experienced prescriptions can optimize the composition of prescriptions which originated from experienced prescriptions, clarify the functions of indications and efficacy features of experienced prescriptions. Case report forms which are normally adapted to clinical new medicine study cannot meet the demand of observational study to optimize experienced prescriptions. This article expounded design features, structure elements and collection timing and proposed requirements for information collection through practice of case report forms in the optimum research on famous TCM doctors’ experienced prescriptions, with a purpose to realize the optimization of experienced prescriptions through observational study on famous TCM doctors’ experienced prescriptions and provide evidence for further clinical research on experienced prescriptions.

Based on traditional Chinese medicine (TCM) herb data of inpatient department and senior famous TCM doctors from many TCM hospitals in China. Existing problems of TCM herb data standardization preprocessing were analyzed in order to explore scientific and reasonable preprocessing program which can provide technical support for the accurate analysis of herbal information. Clinical medicine doctors and herbal pharmacists collaborated and analyzed the real-world TCM herb data collected from multi-regions. In connection with characteristics of TCM, data mining was combined in the analysis of requirement to identify existing problems and explore appropriate problem-solving solutions. The results showed that based on the Pharmacopoeia of the People's Republic of China (PPRC, 2010 version) and regional herb preparing and dispensing guidelines, the herb collection rules, methods and processes were made for the herb data standardization. Herbal data processing program for different regions were formulated. It was concluded that herb data standardization rules and methods made by this plan solved standardization and accuracy of TCM herb data analysis and utilization in multi-area.